diff --git a/examples/juicer_example/README.txt b/examples/juicer_example/README.txt
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+Using Juicer to Run PASTIS on a .hic File
+=========================================
diff --git a/examples/juicer_example/data/Pfalciparum_trophozoite_Ay2014.hic b/examples/juicer_example/data/Pfalciparum_trophozoite_Ay2014.hic
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index 000000000..bf34b0968
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diff --git a/examples/juicer_example/data/counts.bed b/examples/juicer_example/data/counts.bed
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+++ b/examples/juicer_example/data/counts.bed
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+Chr01	1	1	0
+Chr01	2	2	1
+Chr01	3	3	2
+Chr01	4	4	3
+Chr01	5	5	4
+Chr01	6	6	5
+Chr01	7	7	6
+Chr01	8	8	7
+Chr01	9	9	8
+Chr01	10	10	9
+Chr01	11	11	10
+Chr01	12	12	11
+Chr01	13	13	12
+Chr01	14	14	13
+Chr01	15	15	14
+Chr01	16	16	15
+Chr01	17	17	16
+Chr01	18	18	17
+Chr01	19	19	18
+Chr01	20	20	19
+Chr01	21	21	20
+Chr01	22	22	21
+Chr01	23	23	22
+Chr01	24	24	23
+Chr01	25	25	24
+Chr01	26	26	25
diff --git a/examples/juicer_example/data/counts.npy b/examples/juicer_example/data/counts.npy
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diff --git a/examples/juicer_example/juicer_for_pastis.py b/examples/juicer_example/juicer_for_pastis.py
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+"""
+Using a .hic file (output of Juicer) with PASTIS
+================================================
+
+This example showcases how to convert a .hic file output by Juicer into a numpy
+array, output a .bed file for the lengths, and then run PASTIS.
+"""
+
+
+import numpy as np
+import strawC
+import os
+from scipy import sparse
+
+
+##############################################################################
+# Returns a numpy array with counts data from the given .hic file.
+#     val_type : "observed" for raw values; "oe" for observed/expected values
+#     norm : the normalization to apply ("NONE" for no normalization)
+#     hic_file : the path to the .hic file we want to get counts data for
+#     width : the size of the returned counts matrix
+#     chrom1 : the first chromosome
+#     chrom2 : the second chromosome
+#     resolution : the BP resolution
+# --------------------------------------------------------------------------
+def grabRegion(val_type, norm, hic_file, width, chrom1, chrom2, resolution):
+    chrom_range1 = str(chrom1)
+    chrom_range2 = str(chrom2)
+    result = strawC.strawC(val_type, norm, hic_file, chrom_range1,
+                           chrom_range2, 'BP', resolution)
+    row_indices, col_indices, data = list(), list(), list()
+    for record in result:
+        row_indices.append(record.binX)
+        col_indices.append(record.binY)
+        data.append(record.counts)
+        if chrom1 == chrom2 and record.binX != record.binY:
+            row_indices.append(record.binY)
+            col_indices.append(record.binX)
+            data.append(record.counts)
+    row_indices = (np.asarray(row_indices)) / resolution
+    col_indices = (np.asarray(col_indices)) / resolution
+    matrix = sparse.coo_matrix((data, (row_indices.astype(int),
+                               col_indices.astype(int))),
+                               shape=(width, width)).toarray()
+    matrix[np.isnan(matrix)] = 0
+    matrix[np.isinf(matrix)] = 0
+    return matrix
+
+
+##############################################################################
+# Define the path to our .hic file.
+# ---------------------------------
+FILE_PATH = './data/Pfalciparum_trophozoite_Ay2014.hic'
+
+
+##############################################################################
+# Use the grabRegion method to get counts data for the first chromosome
+# in the .hic file at a resolution of 25000. We won't apply any normalization.
+# ----------------------------------------------------------------------------
+counts = grabRegion('observed', 'NONE', FILE_PATH, 26, 1, 1, 25000)
+
+
+##############################################################################
+# Output a .bed file of lengths. Let's call the file "counts.bed".
+# ----------------------------------------------------------------
+with open("./data/counts.bed", "w") as f:
+    the_length = len(counts)
+    for i in range(the_length):
+        curr_line = 'Chr01\t' + str(i + 1) + '\t' + str(i + 1) + '\t'
+        curr_line += str(i)
+        print(curr_line, file=f)
+
+
+##############################################################################
+# Save the counts as a .npy file. Let's call the file "counts.npy".
+# -----------------------------------------------------------------
+np.save("./data/counts.npy", counts)
+
+
+##############################################################################
+# Make the following call using os to run PASTIS with the counts data.
+# The call could be made in command line as well. Note that there are other
+# settings we could run PASTIS with; this is simply one set of those settings.
+# ----------------------------------------------------------------------------
+settings = "pastis-poisson --seed 0 --counts ./data/counts.npy --outdir"
+settings += " ./results --lengths ./data/counts.bed --ploidy 1"
+settings += " --filter_threshold 0.04 --multiscale_rounds 1 --max_iter 50000"
+settings += " --dont-normalize --alpha 3"
+os.system(settings)